Method for validating measurement data

ABSTRACT

A method is provided for validating measurement data, such as data obtained from a scanning electron microscope using in a semiconductor fabrication facility. The method includes applying a signal on a material feature by using a source in a measurement tool having a tool setting parameter, collecting a response signal from the material feature by using a detector in the measurement tool to obtain the measurement data, calculating a simulated response signal by a smart, and validating the measurement data by comparing the collected response signal with the simulated response signal. The system also includes a design database having a design feature, a measurement tool collecting a response signal, and a smart review engine configured to connect the measurement tool and the design database. The smart engine generates a simulated response signal using the design feature and a measurement tool setting parameter so that the measurement is validated by comparing a collected response signal and a simulated response signal.

BACKGROUND

The semiconductor integrated circuit (IC) industry has experiencedexponential growth. Technological advances in IC materials and designhave produced generations of ICs where each generation has smaller andmore complex circuits than the previous generation. In the course of ICevolution, functional density (i.e., the number of interconnecteddevices per chip area) has generally increased while geometry size(i.e., the smallest component (or line) that can be created using afabrication process) has decreased. This scaling down process generallyprovides benefits by increasing production efficiency and loweringassociated costs. Such scaling down has also increased the complexity ofprocessing and manufacturing ICs and, for these advances to be realized,similar developments in IC processing and manufacturing are needed.

The scaling down of an IC device also faces challenges for performing ameasurement on a complicated topography surface of a semiconductorwafer. For example, the complicated topography and the scaled downfeature may cause a measurement error on a measurement tool, such as ascanning electron microscope (SEM) tool. Significant labor and time aretherefore frequently needed to verify the measurement. Accordingly, whatis needed is a method for verifying measurement data more efficientlyand accurately

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is best understood from the following detaileddescription when read with accompanying figures. It is emphasized that,in accordance with the standard practice in the industry, variousfeatures are not drawn to scale and are used for illustration purposeonly. In fact, the dimension of the various features may be arbitrarilyincreased or reduced for clarity of discussion.

FIG. 1 is a diagram of a scanning electron microscope (SEM) tool thatcan be used with one or more embodiments of the present invention.

FIG. 2 is a flow chart of an exemplary method of validating measurementdata, such as data obtained from the SEM tool of FIG. 1.

FIGS. 3A-B are examples of measurements according to one or moreembodiments.

FIGS. 4A-C are examples of validating measurement data according to oneor more embodiments.

FIG. 5 is a system for validating measurement data according to one ormore embodiments of the present invention.

DETAILED DESCRIPTION

The following disclosure provides many different embodiments, orexamples, for implementing different features of the disclosure.Specific examples of components and arrangements are described below tosimplify the present disclosure. These are, of course, merely examplesand are not intended to be limiting. For example, the formation of afirst feature over or on a second feature in the description thatfollows may include embodiments in which the first and second featuresare formed in direct contact, and may also include embodiments in whichadditional features may be formed between the first and second features,such that the first and second features may not be in direct contact. Inaddition, the present disclosure may repeat reference numerals and/orletters in the various examples. This repetition is for the purpose ofsimplicity and clarity and does not in itself dictate a relationshipbetween the various embodiments and/or configurations discussed.

Referring to FIG. 1, an example diagram of a SEM system 100 isillustrated for use with one or more embodiments of the presentinvention. In the present example, the SEM system 100 may also bereferred to as a CDSEM or a CD-SEM system, with CD standing for criticaldimension. Also, it is understood that different types of measurementsystems may also be used with one or more embodiments of the presentinvention. Continuing with the present example, the SEM system 100includes an electron source 102, an anode 104, an electro-optical column106, a stage 108, a detector 110, and a vacuum chamber 112. However,other configurations and inclusion or omission of the system may bepossible.

The electron source 102 provides an electron beam emitted from aconducting material by heating the conducting material connected to acathode to a very high temperature, where the electrons have sufficientenergy to overcome a work function barrier and escape from theconducting material (thermionic sources), or by applying an electricfield sufficiently strong that the electrons tunnel through the workfunction barrier (field emission sources). An anode/cathode 104 combinedwith the cathode provides an electric field to accelerate the electronbeam emitted from the electrons source 102. The electro-optical column106 includes a plurality of electromagnetic apertures, electrostaticlenses, electromagnetic lenses, shaping deflectors and cell selectiondeflectors. The electro-optical column 106 is configured to focus andproject the electron beam to a sample or substrate. The stage 108includes motors, roller guides, and tables. The stage 108 is configuredto secure a sample or substrate on the stage 108 by vacuum and providesthe accurate position and movement of the sample or the substrate in X,Y and Z directions during focus, leveling, and measurement operation.The vacuum chamber 112 is configured to connect to a plurality of pumps,such as mechanical pumps and ion pumps, and provides a high vacuumenvironment for the SEM system 100.

The detector 110 includes a secondary electron detector, an X-raydetector, and/or a backscatter electron detector. Different detectorsare configured for different purposes. For example, a secondary electrondetector detects a signal from interaction between the electron beamprojected on a sample and atoms at or near the surface of the sample. Asa result, the secondary electron detector provides a high resolutionimage of surface of the sample. In the present embodiments, thesecondary electron detector is also used to measure a dimension of thesample. In another example, an X-ray detector detects a signal when theelectron beam projected on the sample removes an inner shell electronfrom the sample and a higher electron to fill the shell and releasesenergy. The X-ray detector detects the composition and abundance ofelements in the sample.

Referring to FIG. 2, a flow chart of a method 200 for validating ameasurement, such as would be obtained from the SEM system 100 of FIG.1, is provided. The method 200 begins at step 202 by receiving anintegrated circuit (IC) design for a device to be measured. The designmay be received, for example, from an IC design house. The IC designhouse may be in independent design house or a design house belonging toa semiconductor fab. In the present embodiments, an IC design is alsoreferred to as design data or IC design data. Continuing with thepresent example, the IC design data includes a design feature whichcorresponds to a feature on a device manufactured (at least partially)in a semiconductor fab. For example, the design feature may include afilm with a thickness deposited on a wafer substrate. In anotherexample, the design feature includes a resist pattern with a dimensionformed on a substrate.

As shown in the figure, the method 200 includes parallel paths of methodsteps. It is understood that a specific sequence of the steps, includingwhether any two steps are done in parallel, is not required, except asexplicitly identified below.

The method 200 proceeds to step 212 by forming a material feature on asubstrate according to the design feature in the IC design data. For thesake of example, the material feature includes a photoresist filmdeposited on a semiconductor wafer. Step 212 may also include forming aresist pattern on the wafer.

The wafer may be in various stages of fabrication, and may includevarious doped features, isolation features, and device features, such asgate structures. In addition, the wafer may include additional films,such as one or more metal layers and/or dielectric layers. The films maybe formed by various techniques, including chemical vapor deposition(CVD), a physical vapor deposition (PVD), an atomic level deposition(ALD), an electric-plating process or a spin-on process.

Referring also FIG. 3A, in the present example, a film 304 is disposedon the substrate 302, and a patterned resist layer 306 is formed on thefilm 304.

The method 200 proceeds to step 214 by performing a measurement on amaterial feature formed on a substrate using a measurement tool togenerate a measurement data of the feature. Step 214 includes measuringdimension of a feature, such as a width. In some embodiments, step 214further includes taking an image of the feature to be measured. In thepresent example, a dimension of a resist pattern may include the widthof a resist line or a space between two resist lines.

In the present embodiments, a dimension of a material feature ismeasured on a measurement or a metrology tool, such as the SEM system100 of FIG. 1 using a secondary electron detector. Referring to theexample of FIG. 3B, top view SEM images 322 a-c of the resist pattern306 a-c respectively, a secondary electron signal line profile 324 byscanning the resist patterns 306 a-c on top using an electron beam, anddimensions d1-d3 for the resist patterns 306 a-c are illustrated. Thedimensions d1-d3 for the resist patterns 306 a-c are obtained by using adistance between two related peeks of the secondary electron signal lineprofile 324 at a threshold, for example, 70%.

A top view SEM image and secondary electron signal line profile of amaterial feature are obtained by scanning the material feature on topusing an electron beam and collecting an emitted secondary electronsusing a secondary electron detector with reference to FIG. 1. Because asemiconductor substrate includes non-conductive material and acomplicated topology, a secondary electron signal line profile mayappear somewhat noise, and a dimension provided by the secondaryelectron signal line profile may be not accurate, and even worse a wrongpeak is chosen due to a high noise. The SEM measurement data needs to bechecked and validated. In a traditional method, the validation of theSEM measurement data is performed by a human. For example, after the SEMmeasurement is taken, a skilled operator, technician, or engineer needsto review a plurality of SEM images and secondary electron signal lineprofiles using his or her eyes. The reviewing is a time-intensiveendeavor, such as collecting the SEM data for building an opticalproximity correction (OPC) database or for calibrating an exposing toolin a semiconductor fab.

Referring again to FIG. 2, after SEM measurement, the method 200proceeds to step 216 by providing the SEM measurement data to a smartreview engine. The SEM measurement data includes SEM images andsecondary electron signal line profiles. The smart engine will bediscussed in more detail below.

As discussed above, the method 200 includes multiple steps that can bedone in various sequences, including some that can be done in parallel.At step 222, a simulation is performed on the smart engine to generate asimulated measurement data. The simulation not only analyzes the designfeature, but also receives measurement parameters. In the presentembodiments, a simulated measurement data is also referred to assimulated data or a simulated result. A design feature may include afilm to be deposited on a substrate, or a pattern or feature to beformed in a substrate. A design feature also includes thickness of thefilm and dimension of the pattern or feature. A simulated data or resultincludes thickness of a film, a profile of a pattern or a dimension of apattern. The measurement parameters include measurement locations usedto measure a feature, measurement magnification, and measurement area.In one embodiment, running a simulation includes generating a simulatedor synthetic secondary electron signal profile or waveform using adesign feature and SEM tool parameters, such as measurement locations,measurement magnification, and measurement area.

Referring to FIG. 4A, in the present example, a design feature 402 for aresist pattern, is a simulated along a scanning electron beam 404. Thisresults in a simulated resist pattern profile 406 for the resistpattern, and a simulated secondary electron signal profile 408 of theresist pattern.

In some embodiments, running a simulation on a smart engine includesgenerating a simulated secondary electron signal profile for a distancebetween two design features using a simulated scanning electron beam.Using a simulated scanning electron beam may include scanning multipletimes by a simulated scanning electron beam to improve a signal to noiseratio for better measurement.

Referring to FIG. 4B, in the present example, a first design feature422, a second design feature 424, a design distance 426 between thefirst design feature 422 and the second design feature 424, a firstsimulated secondary electron signal profile 428 ₁, a second simulatedsecondary electron signal profile 428 ₂, an nth simulated secondaryelectron signal profile 428 _(n), a summed simulated secondary electronsignal profile 430, and a calculated distance 432 on a substrate for thedesign distance 426 are illustrated.

Referring again to FIG. 2, the method 200 proceeds to step 224 byvalidating a measurement data. Step 224 includes reviewing a measureddata and a simulated measurement data on a smart engine. Step 224 alsoincludes comparing the measured data and a simulated measurement data onthe smart engine. In the present embodiments, step 224 includescomparing a collected secondary electron signal profile obtained fromperforming a measurement on a SEM tool with a simulated secondaryelectron signal profile obtained on the smart engine using a SEM toolsetting or measurement parameters. Step 224 further includes comparing aprofile difference between the collected secondary electron signalprofile and the simulated secondary electron signal profile. Step 224also includes comparing a dimension difference between a measurabledimension from the collected secondary electron signal profile and asimulated dimension from the simulated secondary electron signalprofile.

Referring to FIG. 4C, in the present example, a first design feature452, a second design feature 454, a design distance 456 between thefirst design feature 452 and the second design feature 454, a firsttrench pattern 462, a second trench pattern 464, a space 466 between thefirst trench pattern 462 and the second trench pattern 464, and acollected secondary electron signal profile 468 are illustrated. In theembodiment, step 224 includes comparing the simulated secondary electronsignal profile 430 with the collected secondary electron signal profile468.

Referring again to FIG. 2, the method 200 proceeds to step 230 by makinga decision. In the present embodiments, step 230 includes evaluating adifference between a simulated secondary electron signal profile and acollected secondary electron signal profile in a SEM measurement. Forexample, if the collected secondary electron signal profile from afeature formed on a substrate fits the simulated secondary electronsignal profile, a SEM measurement of the feature is considered a validSEM measurement and a measurement value of a dimension is valid. Inanother example, if the collected secondary electron signal profile froma feature formed on a substrate does not fit the simulated secondaryelectron signal profile, a SEM measurement is considered an invalid SEMmeasurement and the feature will be re-measured on a SEM tool again.

The method 200 proceeds to step 232 by finishing the measurement andproviding valid measurement data for further processing. In the presentembodiment, step 232 may include providing valid SEM measurement datafor one or more subsequent processes, such as etching or implantprocess. Step 232 may include providing valid SEM measurement data foran OPC modeling or for calibrating a tool. Additional steps can beprovided before, during, and after the method 200, and some the stepsdescribed can be replaced, eliminated, or moved around for additionalembodiments of the method 200. The method 200 is example embodiments,and is not intended to limit the present invention beyond what isexplicitly recited in the claims.

Referring to FIG. 5, an example of a system 500 for validatingmeasurement data using the method 200 is illustrated. The system 500includes an IC design database 502, a measurement tool 504, smart engine506, and a process database 508. However, other configurations andinclusion or omission of the system 500 may be possible. The system 500is drawn as an example, and is not intended to limit the presentinvention beyond what is explicitly recited in the claims.

The IC design database 502 is configured to connect to the measurementtool 504 and the smart engine 504. The IC design database 502 includesvarious geometrical patterns or features designed for an IC product andbased on the specification of the IC product. The various geometricalpatterns or features form electronic components, such as transistors,resistors, capacitors and the metallic interconnect of these componentsonto a piece of semiconductor, typical silicon. The IC design databasemay include certain assist features, such as features often used forimaging effect, process enhancement, process monitor, and/or maskidentification information. The IC design database 502 provides apattern or a feature to the measurement tool 504 to create a measurementrecipe on the measurement tool 504. The IC design database 502 alsoprovides a pattern or a feature to the smart engine 506 for performing asimulation on the smart engine 506.

The measurement tool 504 is configured to communicate with the ICdesigned database 502 and the smart engine 506. The measurement tool 504includes a source applying a source signal on a sample and a detectorcollecting a response signal from the sample so that the sample ismeasured and a measurement data is obtained from the detector. In thepresent embodiments, the measurement tool 504 includes performing ameasurement on a feature formed on a semiconductor substrate, such asmeasuring a dimension of a feature using a SEM system, such as thesystem 100 of FIG. 1. The measurement tool 504 provides measured dataand secondary electron signal waveform to the smart engine 506 for thesmart engine 506 comparing the measured secondary electron signalwaveform with a simulated one for adjusting to validate the measureddata or not.

The process database 508 includes information relating to one or moreprocesses in the manufacturing facility. For example, the processdatabase 508 may include process control limits and parameters forcontrolling resolution limits for a lithography system. The processdatabase 508 may further include information from the smart engine 506,the measuring tool 504, or from another source (e.g., a processengineer), showing common measurement characteristics for a specificprocess and/or tool. For example, if a tool is known for a certaincharacteristic (e.g., producing slightly bigger CD than targeted, butwithin processing parameters), this characteristic may be included inthe process database 508.

The smart engine 506 includes a standard, general-purpose computerincluding a processor, memory, and interface. The smart engine 506 isconfigured to interface with the process database 508, the IC designdatabase 502 and the measurement tool 504. The computer may be a singlecomputer or a distributed computer, and connects to various componentsof the IC design database 502, the process database 508, and themeasurement tool 504 including but not limited to the connections shownin FIG. 5. The smart engine 506 includes one or more software programsfor performing a simulation and making decisions in one or more steps ofthe method 200. The smart engine software performs the simulation usinga set of input data including a feature from IC design database,measurement tool settings and measurement parameters to generate asimulated data of a measurement. The smart engine 506 also includesperforming a comparison between a measured data and a simulated data andcalculating a difference between the measured data and the simulateddata. The smart engine 506 further includes making a decision tovalidate the measured data if the difference is smaller than apredetermined value or re-measure the feature formed on the substrate ifthe difference is larger than a predetermined value.

In one embodiment, a resist pattern is formed on a substrate accordingto a design layout, a dimension of the resist pattern is measured on aSEM tool using a collected secondary electron signal profile, asimulated secondary electron signal profile is generated on a smartengine according to a design layout using SEM tool settings andmeasurement parameters, a difference between the collected secondaryelectron signal profile and the simulated secondary signal profile iscalculated on the smart engine, and the measured dimension is validatedby the smart engine if the difference is smaller than a predeterminedvalue or within a specification in a fab; and otherwise, the measureddimension is invalidated by the smart engine if the difference is largerthan a predetermined value or out of a specification in a fab.

Thus, the present disclosure describes a method of validating ameasurement data. The method includes receiving a substrate having amaterial feature, where in the material feature is formed on thesubstrate according to a design feature, applying a source signal on thematerial feature by using a source in a measurement tool having a toolsetting parameter, collecting a response signal from the materialfeature by using a detector in the measurement tool to obtain themeasurement data, calculating a simulated response signal from thedesign feature by a smart engine using the tool setting parameter, andvalidating the measurement data by comparing the collected responsesignal with the simulated response signal. Applying a source signalincludes applying an optical, electronic, mechanical signal, orcombination thereof. Collecting a response signal includes collecting aresponded optical, electronic, mechanical signal, or combinationthereof. Collecting a response signal further includes collecting asecondary electron signal on a scanning electron microscope (SEM) tool.Calculating the simulated response signal includes calculating asimulated response optical, electronic, mechanical signal, orcombination thereof. Calculating the simulated response signal furtherincludes calculating a simulated secondary electron signal. Validatingthe measurement data includes calculating a difference between thecollected response signal and the simulated response signal. Validatingthe measurement data further includes evaluating the difference.Validating the measurement data further includes passing the measurementif the difference is smaller than a predetermined value. Validating themeasurement data further includes performing a re-measurement if thedifference is larger than a predetermined value.

In one or more embodiments, a method of validating a measurement data isdescribed. The method includes receiving a design data having designfeature, wherein a material feature is formed on a substrate accordingto the design feature, performing a measurement on the material featureby applying an electron beam on the material feature and collecting asecondary electron signal from the material feature using a scanningelectron microscope (SEM) tool having a tool setting parameter,executing a simulation on a smart engine using the design feature andthe tool setting parameter to generate a simulated secondary electronsignal, and validating the measurement by comparing the collectedsecondary electron signal and the simulated secondary electron signal.Validating the measurement includes calculating a difference between thecollected secondary electron signal and the simulated secondary electronsignal. Validating the measurement further includes evaluating thedifference. Validating the measurement further includes passing themeasurement if the difference is smaller than a predetermined value.Validating the measurement further includes performing a re-measurementif the difference is larger than a predetermined value.

In some embodiments, a system for validating a measurement data isdescribed. The system includes a design database having a designfeature, where a material feature is formed on a substrate according tothe design feature, a measurement tool configured to connect the designdatabase, wherein the measurement tool having a tool setting parameterincludes a source generating a source signal applied on the materialfeature and a detector collecting a response signal from the materialfeature so that a measurement of the material feature is performed onthe measurement tool, and a smart review engine configured to connectthe measurement tool and the design database, wherein the smart enginegenerates a simulated response signal using the design feature and thetool setting parameter so that the measurement is validated by comparingthe response signal and the simulated response signal. The source signalincludes an optical, mechanical, electronic signal, or combinationthereof. The response signal includes an optical, mechanical, electronicsignal, or combination thereof. The simulated response signal includes asimulated response optical, mechanical, electronic signal, orcombination thereof. The simulated response signal further includes asimulated secondary electron signal profile.

The foregoing outlines features of several embodiments so that thoseskilled in the art may better understand the aspects of the presentdisclosure. Those skilled in the art should appreciate that they mayreadily use the present disclosure as a basis for designing or modifyingother processes and structures for carrying out the same purposes and/orachieving the same advantages of the embodiments introduced herein.Those skilled in the art should also realize that such equivalentconstructions do not depart from the spirit and scope of the presentdisclosure, and that they may make various changes, substitutions, andalterations herein without departing from the spirit and scope of thepresent disclosure.

What is claimed is:
 1. A method for forming features on a substrate, themethod comprising: receiving the substrate having a material feature,where in the material feature is formed on the substrate according to adesign feature; applying a source signal on the material feature byusing a source in a measurement tool having a tool setting parameter;collecting a response signal from the material feature by using adetector in the measurement tool to obtain measurement data; calculatinga simulated response signal from the design feature by a smart engineusing the tool setting parameter; and validating the measurement data bycomparing the collected response signal with the simulated responsesignal.
 2. The method of claim 1, wherein applying a source signalincludes applying an optical, electronic, or mechanical signal.
 3. Themethod of claim 2, wherein collecting a response signal includescollecting a responded optical, electronic, or mechanical signal.
 4. Themethod of claim 3, further comprising collecting a secondary electronsignal on a scanning electron microscope (SEM) tool.
 5. The method ofclaim 1, wherein calculating the simulated response signal includescalculating a simulated response optical, electronic, or mechanicalsignal.
 6. The method of claim 5, further comprising calculating asimulated secondary electron signal.
 7. The method of claim 1, whereinvalidating the measurement data includes calculating a differencebetween the collected response signal and the simulated response signal.8. The method of claim 7, further comprising evaluating the differenceto determine if it is within a predetermined value.
 9. The method ofclaim 8, further comprising presenting the measurement as a goodmeasurement if the difference is smaller than the predetermined value.10. The method of claim 8, further comprising performing are-measurement if the difference is larger than the predetermined value.11. A method comprising: receiving a design data having design feature,wherein a material feature is formed on a substrate according to thedesign feature; performing a measurement on the material feature byapplying an electron beam on the material feature and collecting asecondary electron signal from the material feature using a scanningelectron microscope (SEM) tool having a tool setting parameter;executing a simulation on a smart engine using the design feature andthe tool setting parameter to generate a simulated secondary electronsignal; and validating the measurement by comparing the collectedsecondary electron signal and the simulated secondary electron signal.12. The method of claim 11, wherein validating the measurement includescalculating a difference between the collected secondary electron signaland the simulated secondary electron signal.
 13. The method of claim 12,further comprising comparing the difference to a predetermined value.14. The method of claim 13, wherein further comparing passing themeasurement if the difference is smaller than the predetermined value.15. The method of claim 13, wherein further comprising performing are-measurement if the difference is larger than the predetermined value.16. A system for validating a measurement data, the system comprising: adesign database having a design feature, where a material feature isformed on a substrate according to the design feature; a measurementtool configured to connect the design database, wherein the measurementtool having a tool setting parameter includes a source generating asource signal applied on the material feature and a detector collectinga response signal from the material feature so that a measurement of thematerial feature is performed on the measurement tool; and a smartreview engine configured to connect the measurement tool and the designdatabase, wherein the smart engine generates a simulated response signalusing the design feature and the tool setting parameter so that themeasurement is validated by comparing the response signal and thesimulated response signal.
 17. The system of claim 16, wherein thesource signal includes an optical, mechanical, electronic signal, orcombination thereof.
 18. The system of claim 16, wherein the responsesignal includes an optical, mechanical, electronic signal, orcombination thereof.
 19. The system of claim 17, wherein the simulatedresponse signal includes a simulated response optical, mechanical,electronic signal, or combination thereof.
 20. The system of claim 19,further comprising a simulated secondary electron signal profile.